Assessment of occurrence, partitioning and ecological risk for 144 steroid hormones in Taihu Lake using UPLC-MS/MS with machine learning model.

Autor: Zhao L; Beijing Key Lab for Source Control Technology of Water Pollution, College of Environmental Sciences & Engineering, Beijing Forestry University, Beijing, 100083, China., Wang C; China CDC Key Laboratory of Environment and Human Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, 100021, China., Sun F; State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing, 100012, China., Liao H; State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing, 100012, China., Chang H; Beijing Key Lab for Source Control Technology of Water Pollution, College of Environmental Sciences & Engineering, Beijing Forestry University, Beijing, 100083, China. Electronic address: changh@bjfu.edu.cn., Jia X; NHC Key Laboratory of Food Safety Risk Assessment, China National Center for Food Safety Risk Assessment, Beijing, 100021, China. Electronic address: jiaxudong@cfsa.net.cn.
Jazyk: angličtina
Zdroj: Chemosphere [Chemosphere] 2024 Apr; Vol. 354, pp. 141598. Date of Electronic Publication: 2024 Mar 01.
DOI: 10.1016/j.chemosphere.2024.141598
Abstrakt: Steroid hormones (SHs) have attracted mounting attention due to their endocrine-disrupting effects on humans and aquatic organisms. However, the lack of analytical methods and toxicity data for a large number of SHs has limited the effective management of SH contamination in the water-sediment systems. In this study, we developed a highly sensitive analytical method for the simultaneous quantification of 144 SHs to investigate their occurrence, spatial distribution and partitioning in the water and sediment in Taihu Lake. The results showed that the total concentrations of SHs in water and sediment were 366.88-998.23 ng/L (mean: 612.84 ng/L) and 17.46-150.20 ng/g (mean: 63.41 ng/g), respectively. The spatial distribution of SHs in Taihu Lake might be simultaneously influenced by the pollution sources, lake hydrodynamics, and sediment properties. The sediment-water partitioning result implied that 28 SHs were in dynamic equilibrium at the water-water interface. In addition, 22 and 12 SHs tended to spread to water and settle into sediment, respectively. To assess the ecological risk of all SHs, a robust random forest model (R 2  = 0.801) was developed to predict the acute toxicity of SHs for which toxicity data were not available from publications. Risk assessment showed that SHs posed a high ecological risk throughout Taihu Lake, with the highest risk in the northwestern areas. Estrone, 17β-estradiol and 17α-ethynylestradiol were the dominant risk contributors and were therefore recommended as the priority SHs in Taihu Lake. This work provided a valuable dataset for Taihu Lake, which would help to provide guidance and suggestions for future studies and be useful for the government to develop the mitigation and management measures.
Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
(Copyright © 2024 Elsevier Ltd. All rights reserved.)
Databáze: MEDLINE
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